chore: import upstream snapshot with attribution

2026-07-13 13:33:03 +08:00
commit 5b57521aa1
8226 changed files with 3425766 additions and 0 deletions
@@ -0,0 +1,78 @@
+//
+//  ShapeReduction.cpp
+//  MNN
+//
+//  Created by MNN on 2019/01/10.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include "shape/SizeComputer.hpp"
+#include "core/Macro.h"
+#include "core/TensorUtils.hpp"
+
+namespace MNN {
+static int _getRealAxis(int axis, int n) {
+    if (axis < 0) {
+        return axis + n;
+    }
+    return axis;
+}
+class ReductionComputer : public SizeComputer {
+public:
+    virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs,
+                               const std::vector<Tensor*>& outputs) const override {
+        MNN_ASSERT(1 == inputs.size() || 2 == inputs.size());
+        MNN_ASSERT(1 == outputs.size());
+
+        auto output                                       = outputs[0];
+        TensorUtils::getDescribe(output)->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
+        auto reduce                                       = op->main_as_ReductionParam();
+        output->buffer().type = inputs[0]->buffer().type;
+        if (nullptr == reduce->dim() && inputs.size() == 1) {
+            if (reduce->keepDims()) {
+                output->buffer().dimensions = inputs[0]->dimensions();
+                for (int i = 0; i < inputs[0]->dimensions(); i++) {
+                    output->setLength(i, 1);
+                }
+            } else {
+                output->buffer().dimensions = 0;
+            }
+            return true;
+        }
+        uint8_t reduceMask[MNN_MAX_TENSOR_DIM];
+        ::memset(reduceMask, 0, sizeof(uint8_t) * MNN_MAX_TENSOR_DIM);
+        if (nullptr != reduce->dim()) {
+            for (int i = 0; i < reduce->dim()->size(); ++i) {
+                reduceMask[_getRealAxis(reduce->dim()->data()[i], inputs[0]->dimensions())] = 1;
+            }
+        } else {
+            auto input1 = inputs[1];
+            auto size   = input1->elementSize();
+            auto dims   = input1->host<int32_t>();
+            for (int i = 0; i < size; ++i) {
+                reduceMask[_getRealAxis(dims[i], inputs[0]->dimensions())] = 1;
+            }
+        }
+
+        auto input                = inputs[0];
+        const int inputDimensions = input->dimensions();
+
+        int offset = 0;
+        for (int i = 0; i < inputDimensions; ++i) {
+            if (1 == reduceMask[i]) {
+                if (reduce->keepDims()) {
+                    output->buffer().dim[offset].extent = 1;
+                    offset++;
+                }
+                continue;
+            }
+            output->buffer().dim[offset].extent = input->length(i);
+            offset++;
+        }
+        output->buffer().dimensions = offset;
+        return true;
+    }
+};
+
+REGISTER_SHAPE_INPUTS(ReductionComputer, OpType_Reduction, {1});
+} // namespace MNN